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A scheduling and binding heuristic for high-level synthesis of fault-tolerant FPGA applications

机译:一种用于容错FPGA应用程序高级综合的调度和绑定启发式方法

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Space computing systems commonly use field-programmable gate arrays to provide fault tolerance by applying triple modular redundancy (TMR) to existing register-transfer-level (RTL) code. Although effective, this approach has a 3× area overhead that can be prohibitive for many designs that often allocate resources before considering effects of redundancy. Although a designer could modify existing RTL code to reduce resource usage, such a process is time consuming and error prone. Integrating redundancy into high-level synthesis is a more attractive approach that enables synthesis to rapidly explore different tradeoffs at no cost to the designer. In this paper, we introduce a scheduling and binding heuristic for high-level synthesis that explores tradeoffs between resource usage, latency, and the amount of redundancy. In many cases, an application will not require 100% error correction, which enables significant flexibility for scheduling and binding to reduce resources. Even for applications that require 100% error correction, our heuristic is able to explore solutions that sacrifice latency for reduced resources, and typically save up to 47% when relaxing the latency up to 2×. When the error constraint is reduced to 70%, our heuristic achieves typical resource savings ranging from 18% to 49% when relaxing the latency up to 2×, with a maximum of 77%. Even when comparing with optimized RTL designs, our heuristic uses up to 61% fewer resources than TMR.
机译:空间计算系统通常使用现场可编程门阵列通过将三重模块冗余(TMR)应用于现有的寄存器传输级(RTL)代码来提供容错能力。尽管有效,但这种方法具有3倍的区域开销,这对于许多在考虑冗余影响之前经常分配资源的设计是不可行的。尽管设计人员可以修改现有的RTL代码以减少资源使用,但是这样的过程既耗时又容易出错。将冗余集成到高级综合中是一种更具吸引力的方法,它使综合能够快速探索各种折衷方案,而对设计人员却没有任何成本。在本文中,我们介绍了用于高级综合的调度和绑定启发式方法,该方法探索了资源使用,延迟和冗余量之间的折衷。在许多情况下,应用程序将不需要100%的纠错,这为调度和绑定提供了极大的灵活性,以减少资源。即使对于需要100%纠错的应用程序,我们的启发式方法也能够探索牺牲延迟以减少资源的解决方案,并且在将延迟降低2倍时通常可以节省多达47%的时间。当错误约束降低到70%时,我们的启发式方法在将等待时间放宽至2倍时最多可节省18%到49%的资源,最多可节省77%。即使与优化的RTL设计进行比较,我们的启发式方法所使用的资源也比TMR减少多达61%。

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